Brainmap: Human Neocortical Rhythms: From Mechanism to Meaning via Computational Neural Modeling
Stephanie R. Jones, PhD.
Department of Neuroscience,
Low frequency neocortical rhythms are among the most prominent activity measured in human brain imaging signals such as electro- and magneto- encephalography (EEG/MEG). Elucidating the role that these dynamics play in perception, cognition and action is a key challenge of modern neuroscience. We have recently combined MEG, computational neural modeling, and electrophysiological recordings in rodents and monkeys to explore the functional relevance and mechanistic underpinnings of rhythms in primary somatosensory cortex (SI), containing Alpha (7-14Hz) and Beta (15-29Hz) components. In this talk, I will review our findings showing this rhythm impacts tactile detection, changes with healthy aging and practice, and is modulated locally and in coordination with frontal cortex during attention. Constrained by the human imaging data, our biophysically principled computational modeling work has led to a novel prediction on the origin of this rhythm predicting that it emerges from the combination of two stochastic ~10 Hz thalamic burst drives to the granular/infragranular and supragranular cortical layers. Relative Alpha/Beta expression depends on the strength and delay between the thalamic drives. This model is able to accurately reproduce numerous key features of the human rhythm and proposes a specific mechanistic link to changes with attention and perception. Further, initial electrophysiological recordings in rodents and monkeys support out hypotheses and suggest a role for pallidal thalamus in coordinating the rhythmicity, with relevance to understanding disrupt Beta rhythmicity in Parkinson’s Disease.